The tech industry is buzzing about artificial intelligence, machine learning, and neural networks. AI is rising in the field of automated software testing as well.
Test automation has evolved remarkably. QA teams have greatly aided in minimizing the possibility of human error. According to a survey, application testers have incorporated automated testing into their processes at an overwhelming majority of 97%. AI testing tools have taken over the burden of handling repetitive tasks, allowing the team to devote more time to the more complex and crucial tasks.
Selecting the best automation testing tool is essential to ensure the success of any testing automation strategy, even though there are many options for automating tests. We have hand-picked the best 10 AI testing tools to peruse and consider.
What Are AI-Powered Testing Tools?
AI testing tools are software testing tools that utilize artificial intelligence (AI) systems to enhance the testing process. They assist QA teams in routine tasks (such as test creation and result management) and more complex cognitive tasks previously only achievable with human intelligence.
AI-powered testing tools have achieved a major milestone on reaching level 5 of the Autonomous Testing Benchmark for software quality assurance.
List Of Top AI Automation Testing Tools
Many businesses use artificial intelligence (AI) in their software testing processes. Let’s examine some of the widely known AI testing tools available.
1. ACCELQ
ACCELQ, a powerful AI-driven codeless tool, enables multi-channel test automation for web, mobile, desktop, API, and backend. Incorporating automation of business processes into all stack layers enables continuous test automation and ensures complete business assurance.
Key Features
- Rapidly develops automated tests while reducing time spent on routine upkeep.
- One centralized place for automating web, API, mobile, and desktop.
- Aligning DevOps and Agile through automation during sprints.
- Enable non-programming testers to automate manual testing procedures.
- Verify operational procedures using a graphical model of the application.
- Easily accommodate frequent updates by using self-repairing, autonomous test automation.
- Artificial intelligence is used to produce test cases and test data quickly.
2. TestGrid
The TestGrid platform, part of the AI Test Automation Tools suite, offers features such as automated testing, performance testing, API testing, and security testing. Testgrid’s on-demand access to hundreds of real Android and iOS devices allows you to test your app on various devices.
Key Features
- TestGrid AI will automatically generate test cases if you provide a test scenario written in plain English.
- You can use a variety of authentic Android and iOS devices.
- You should test your app’s battery life, network strength, responsiveness, and swipe gestures.
- Create your test cases without modifying any code.
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3. TestCraft
TestCraft builds an AI-driven test automation platform on top of Selenium for continuous and regression testing. You can also use it to keep tabs on your favourite websites. AI technology can automatically update the app, saving time and money on maintenance.
TestCraft’s greatest strength is its drag-and-drop interface for creating automated Selenium-based tests. Various platforms and browsers can also use them in tandem. You don’t need to know how to code.
Key Features
- The interface is easy to navigate and has drag-and-drop features for building automated tests.
- You can perform parallel testing in various browsers and OS configurations without extensive coding knowledge.
- TestCraft’s On-the-Fly mode creates a test model from individual test scenarios, making it easier to reuse test steps.
- The artificial intelligence algorithm accurately recognizes web elements and quickly adjusts to new web applications.
4. Testsigma
Testsigma is highly ranked when it comes to AI testing. Analysts and automation engineers can use this tool to develop automated tests for web, mobile, desktop, and API applications. Additionally, it can self-correct severe mistakes. This tool enables manual testers and team leads to run tests simultaneously and effectively.
Key Features
- With NLP, one can easily make a test by writing a few sentences in standard English without needing to code.
- It eliminates the need for local setup because it is web-based.
- Enables the automation of web, mobile, desktop, and API tests.
- The control panel is amazing.
- Intelligent intuition and self-repairing abilities are present.
- Testing purposes require capabilities based on actual data.
- The features include scheduling and automating reports.
5. Mabl
The graphical user interface of Mabl is robust and user-friendly. It is one of the AI tools for testing, but it only performs a little code testing. Teams with tight schedules can rapidly test using the tool. It executes full-stack tests from the initial coding to the final testing. At the same time, the tool facilitates communication between clients and managers throughout the entire process.
Key Features
- Low-code testing supports quality assurance by freeing up time.
- Intelligent intuition and self-repairing abilities are present.
- Testing purposes require capabilities based on actual data.
- Comprehensive end-to-end testing with powerful API access.
- Developers can gain insight from data.
- The interface is user-friendly.
6. Applitools
Applitools, an AI-based test automation tool, traditionally tests, monitors, and manages apps’ graphical interfaces. Engineers and digital transformation teams favor the tool for its versatility. Its extensive use of AI and ML makes it well-known for its speed and accuracy in visual testing.
Key Features
- Graphically represents test results.
- AI powers Applitools to reliably identify material differences and categorize them as either relevant or irrelevant.
7. Sauce Labs
Sauce Labs is another AI-powered tool with extensive testing capabilities. You can use it from the beginning of software development, guaranteeing a constant testing cycle. All major browsers and operating systems work well with this cross-platform tool, making it ideal for automating functional tests. Designers and coders comprehend the inner workings of a system or website with the help of this method. Additionally, it maximizes your time by using parallel testing.
Key Features
- The system includes tracking and reporting errors, performing regular checks, and compiling comprehensive reports.
- It serves as a universal testing platform for web browsers and operating systems.
- The software includes a graphical interface that allows users to run automated UI and visual tests.
- The company provides a mobile app for testing on actual and virtual mobile devices.
- The tool includes API testing and monitoring for thorough API evaluation.
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8. Functionize
The technology for automated testing Functionize uses the cloud to host functional, performance, and load testing. Additionally, this instrument uses machine learning and artificial intelligence to expedite testing development, diagnosis, and upkeep.
One of the tool’s many strengths is the convenience of requiring little effort to think before conducting a test. NLP automatically generates the desired test cases when entering them in plain English. In minutes, it can generate thousands of tests from any desktop or mobile browser.
Key Features
- Lightning-fast creation
- AI-assisted maintenance
- Fast debugging & easy edits
- Adaptive execution at scale
9. Katalon Platform
Developers with little to no engineering or coding experience can use Katalon Platform to create, manage, execute, maintain, and report on tests for web, API, desktop, and mobile applications in a wide range of environments.
Key Features
- Appearance matching is used to locate UI elements, rather than object attributes.
- By analyzing the execution history of a test and learning its pattern of status changes, one can determine the test’s unreliability.
- Automatically classifies failed test cases by root cause and suggests fixes.
- Automatically fixes broken element locators and reuses them in subsequent test runs, reducing the amount of time spent on maintenance.
10. TestComplete
TestComplete has dynamic and easy-to-use UI testing elements. It includes checkpoints to ensure the quality of the provided images, tables, and app features. The script-free app allows you to trigger tests using keywords or a simple record-and-play workflow. Additionally, the software enables data-driven testing for desktop and mobile UIs. Additionally, it analyzes test reports and generates a report.
Key Features
- It supports simultaneous testing of mobile, desktop, and web applications.
- Includes scalable mobile and web testing.
- You can use automated user interface testing repeatedly for different projects.
- Data and algorithms form the basis of reporting and analysis instruments.
Advantages Of AI In Software Testing
- AI-powered tools can complete regression, functional, and performance testing much more quickly and efficiently than human testers.
- AI-powered tools can improve software testing quality by finding flaws and errors that would otherwise go unnoticed.
- Reducing the need for expensive human testers can save money by automating routine tasks.
- Using AI-powered tools early on in the process can make fixing defects and bugs in software easier and ensure smoother product launches.
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Conclusion
There are many different options for automating the testing process. Some people offer their services for free while others charge money. Each device possesses its own special qualities. Testers often choose test automation tools that meet the needs of their projects because there is such a wide variety of test automation tools available. You must select the appropriate tool for your work.
